Skip to main content

Advertisement

Volume 16 Supplement 3

Selected articles from the 5th Translational Bioinformatics Conference (TBC 2015): medical informatics and decision making

Research

Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. Articles have undergone the journal’s standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.

Tokyo, Japan7-9 November 2015

Conference website

Edited by Ju Han Kim and Maricel Kann 

Other articles from the conference have been published as a supplement to BMC Medical Genomics.

  1. The study on disease-disease association has been increasingly viewed and analyzed as a network, in which the connections between diseases are configured using the source information on interactome maps of bio...

    Authors: Yonghyun Nam, Myungjun Kim, Kyungwon Lee and Hyunjung Shin

    Citation: BMC Medical Informatics and Decision Making 2016 16(Suppl 3):72

    Content type: Research

    Published on:

  2. In biomedical research, data sharing and information exchange are very important for improving quality of care, accelerating discovery, and promoting the meaningful secondary use of clinical data. A big concer...

    Authors: Haoyi Shi, Chao Jiang, Wenrui Dai, Xiaoqian Jiang, Yuzhe Tang, Lucila Ohno-Machado and Shuang Wang

    Citation: BMC Medical Informatics and Decision Making 2016 16(Suppl 3):89

    Content type: Research

    Published on:

  3. Accurately assessing pain for those who cannot make self-report of pain, such as minimally responsive or severely brain-injured patients, is challenging. In this paper, we attempted to address this challenge b...

    Authors: Lei Yang, Shuang Wang, Xiaoqian Jiang, Samuel Cheng and Hyeon-Eui Kim

    Citation: BMC Medical Informatics and Decision Making 2016 16(Suppl 3):73

    Content type: Research

    Published on:

  4. Nearest neighbor (NN) imputation algorithms are efficient methods to fill in missing data where each missing value on some records is replaced by a value obtained from related cases in the whole set of records...

    Authors: Lorenzo Beretta and Alessandro Santaniello

    Citation: BMC Medical Informatics and Decision Making 2016 16(Suppl 3):74

    Content type: Research

    Published on: